Note: Intro -- Preface -- Contents -- Introduction to 20 Years of Grammatical Evolution -- 1 Evolutionary Computation -- 2 Grammatical Evolution -- 2.1 Grammars and Evolutionary Computation -- 3 Crash Course in Grammatical Evolution -- 3.1 Mapping -- 3.2 Alternative Grammars -- 3.2.1 Attribute Grammars -- 4 Twenty Years of Grammatical Evolution -- 5 The State of the Art -- 5.1 Grammars -- 5.2 Genetic Operators -- 5.2.1 Initialisation -- 5.3 Parameter Settings -- 5.4 Variants -- 6 Contents of This Book -- 7 Summary -- References -- Understanding Grammatical Evolution: Grammar Design -- 1 Introduction -- 2 Previous Work -- 3 Grammar Design -- 3.1 Balanced Grammars -- 3.2 Unlinked Productions -- 3.3 Reduced Non-terminals -- 3.4 Grammar Biases -- 3.5 Infix/Prefix Notation -- 3.6 Compromise Grammars -- 4 Transformations Analysis -- 4.1 Initialisation Biases -- 4.2 Random Walk Biases -- 4.3 Termination Biases -- 4.4 Performance Biases -- 5 Performance Analysis -- 5.1 Problems -- 5.2 Grammars -- 5.2.1 Keijzer-6 -- 5.2.2 Vladislavleva-4 -- 5.2.3 Shape Match (Hard) -- 5.3 Experimental Setup -- 5.4 Results -- 5.4.1 Significance and Test Results -- 5.5 Analysis -- 6 Conclusions -- References -- On the Non-uniform Redundancy of Representationsfor Grammatical Evolution: The Influence of Grammars -- 1 Introduction -- 2 Bias of Representations in Grammatical Evolution -- 3 Balanced, Explosive, and Collapsing Grammars -- 4 Experimental Setup -- 5 Results and Analysis -- 5.1 Binary Grammars -- 5.2 Unary Grammars -- 5.3 Trinary Grammars -- 5.4 Mixed Arity Grammars -- 6 Conclusions -- References -- Mapping in Grammatical Evolution -- 1 Introduction -- 2 πGE: Position Independent Mapping in GE -- 2.1 Position Independent Mapping -- 2.1.1 πGE Mapping Example -- 2.2 Connectivity of Representation -- 2.2.1 GE Versus πGE Genotypes -- 2.2.2 Search Landscapes. , 2.2.3 Mutate and Store -- 2.3 Phenotypic Landscape Visualisations -- 2.3.1 Limitations -- 2.3.2 Discussion -- 2.4 Expansion Order in πGE -- 2.5 πGE Summary -- 3 TAGE: Tree Adjunct Grammatical Evolution -- 3.1 Tree Adjunct Grammars -- 3.1.1 From CFG to TAG -- 3.2 TAG Genotype-Phenotype Mapping -- 3.3 Tree Composition Operations for Linear Mapping -- 3.4 Genotype-Phenotype Mapping -- 3.4.1 TAGE Mapping Example -- 3.5 Operators -- 3.6 Limitations of TAGE -- 3.6.1 Generating TAGE Tree Stubs -- 3.7 Connectivity -- 3.8 Summary -- 4 Conclusions -- References -- Theory of Disruption in GE -- 1 Introduction -- 2 Background -- 3 Formal Description of GE -- 3.1 GE Components -- 3.1.1 Chromosome to Production Choice Sequence -- 3.1.2 Genotype to Phenotype: Integer Sequence to Word -- 3.1.3 Output to Fitness Value -- 3.2 Representation Spaces in GE -- 4 Theory of Disruption in GE -- 4.1 Change in the Chromosome -- 4.1.1 Codon Change -- 4.1.2 Integer Production Choice Change -- 4.1.3 Derivation Change -- 4.1.4 Change Grammar Design -- 4.1.5 Multiple Changes in the Chromosome -- 4.2 Input Change and Output Preservation -- 4.2.1 Change Effects -- 4.2.2 Branch Change -- 4.2.3 Ripple -- 4.3 Disruption in a GE Population -- 4.3.1 GE Schema -- 5 Discussion -- 6 Conclusions and Future Work -- References -- Structured Grammatical Evolution: A Dynamic Approach -- 1 Introduction -- 2 Background -- 2.1 Grammatical Evolution -- 2.2 Structured Grammatical Evolution -- 3 Dynamic Structured Grammatical Evolution -- 3.1 Representation -- 3.2 Initialisation -- 3.3 Mapping Function -- 3.4 Genetic Operators -- 3.4.1 Mutation -- 3.4.2 Recombination -- 4 Classical Problems -- 4.1 Experimental Setup -- 4.2 Benchmark Description -- 4.2.1 Quartic Symbolic Regression -- 4.2.2 Boston Housing Problem -- 4.2.3 Pagie Polynomial Regression -- 4.2.4 Harmonic Curve Regression. , 4.2.5 5-Bit Parity -- 4.2.6 11-Bit Boolean Multiplexer -- 4.2.7 Santa Fe Ant Trail -- 4.3 Experimental Results -- 5 NeuroEvolution -- 5.1 Experimental Setup -- 5.2 Benchmark Description -- 5.3 Experimental Results -- 6 Conclusions -- References -- Geometric Semantic Grammatical Evolution -- 1 Introduction -- 2 Geometric Semantic Genetic Programming -- 2.1 Geometric Semantic Operators -- 3 Foundations for Geometric Semantic Operators for GE -- 3.1 Compositional Semantics -- 3.2 Compositionality of the GE Mapping -- 4 Derivation of Geometric Semantic Operators for GE -- 4.1 Operators for Boolean Domains -- 4.2 Operators for Arithmetic Domains -- 4.3 Operators for Classifier Domains -- 5 An Efficient Implementation of GSGE -- 6 Computational Experiments -- 7 Discussion -- 8 Summary -- References -- GE and Semantics -- 1 A Comprehensible Introduction to Semantics in Formal Languages -- 1.1 Syntax vs. Semantics -- 1.2 Machines and Computability -- 1.3 Grammars and Languages -- 1.3.1 Let Us Try to Formalize -- 2 Breaking the Expressive Limits of Context-Free Models with a Semantic Approach -- 2.1 GE and Semantics -- 2.2 Attribute Grammars -- 2.2.1 Introducing Attribute Grammars -- 2.2.2 Propagation Mechanisms in Attribute Grammars -- 2.2.3 Attribute Grammar Examples -- 2.2.4 Comparison with Chomsky Type-0 Grammars -- 2.3 Christiansen Grammars -- 2.3.1 A Short Historical and Academic Introduction -- 2.3.2 Partial Formalization for CG -- 2.3.3 Conclusions -- 2.4 AGE and CGE -- 2.4.1 How We Extend GE -- 2.4.2 Previous Works -- 3 Most Relevant Conclusions -- 3.1 In General -- 3.2 AGE and CGE -- References -- Multi- and Many-Threaded Heterogeneous Parallel Grammatical Evolution -- 1 Introduction -- 2 Multi-Threaded Parallel GE -- 2.1 Startup Tasks -- 3 Many-Threaded Parallel GE -- 3.1 Program-Level Parallelism: PP -- 3.2 Data-Level Parallelism: DP. , 3.3 Program- and Data-Level Parallelism: PDP -- 3.4 Iteration's Best Program -- 4 Performance Analysis -- 4.1 Case Study -- 4.1.1 Multi-Threaded + Sequential -- 4.1.2 Sequential + Many-Threaded -- 4.1.3 Multi-Threaded + Many-Threaded -- 4.2 In-Depth Kernel Analysis -- 4.2.1 Results -- 5 Conclusions -- References -- Comparing Methods to Creating Constants in GrammaticalEvolution -- 1 Introduction -- 2 Background -- 3 Experiments -- 3.1 Grammars Used for Experiments -- 3.2 Problem Suite and Evolutionary Parameters -- 3.3 Results -- 3.4 Discussion -- 4 Conclusions -- References -- Grammatical Evolution in Finance and Economics: A Survey -- 1 Introduction -- 1.1 Structure of Chapter -- 2 Financial Trading -- 2.1 Fundamental Analysis -- 2.2 Technical Analysis -- 2.3 Arbitrage -- 2.4 GE and Trading -- 2.4.1 Applications of GE for Trading System Design -- 2.5 Intraday Data -- 2.6 Foreign Exchange Markets -- 2.7 Sentiment Analysis -- 2.8 Fitness Function Design -- 2.8.1 Trade Execution -- 2.9 Market Structure -- 2.10 GE and Trade Execution -- 3 Credit Risk Modelling -- 3.1 Bankruptcy Prediction -- 3.2 Bond Rating Prediction -- 3.3 Other Related Problems in Finance -- 4 Other Finance and Economics Applications of GE -- 4.1 Supply Chain Management -- 4.2 Tax Non-Compliance Detection -- 4.3 Corporate Strategy -- 5 The Future -- References -- Synthesis of Parallel Programs on Multi-Cores -- 1 Introduction -- 2 Related Research -- 2.1 Evolutionary Techniques for Recursion -- 2.2 Evolutionary Techniques for Sorting -- 2.3 Automatic Evolution of Parallel Programs -- 3 Grammatical Automatic Parallel Programming -- 3.1 GAPP for Parallel Recursion -- 3.2 GAPP for Parallel Iterative Sorting -- 4 Experiments -- 4.1 GAPP Variants -- 5 Results -- 5.1 Recursion -- 5.2 Iterative Sorting -- 6 Enhancements in GAPP -- 6.1 Recursion -- 6.2 Iterative Sorting -- 7 Conclusion. , References -- Design, Architecture, and Engineering with Grammatical Evolution -- 1 Introduction -- 1.1 Grammatical Representations for Evolutionary Design -- 1.2 Evaluation in Evolutionary Design -- 1.3 Chapter Overview -- 2 Grammatical Representations for Evolutionary Design -- 2.1 Lindenmayer Systems -- 2.1.1 GENR8 -- 2.2 Shape Grammars -- 2.3 Other Representations -- 2.3.1 Higher Order Functions -- 2.3.2 Graph Grammars -- 3 Evaluation in Evolutionary Design -- 3.1 Interactive Evolutionary Design -- 3.1.1 Representations Revisited -- 3.2 Engineering Applications of Evolutionary Design -- 3.2.1 Engineering Constraints -- 3.2.2 Engineering Applications of Grammatical Evolution -- 3.2.3 Multiple Objectives in Engineering Optimisation -- 3.3 Optimisation vs Design Exploration -- 4 Conclusions -- References -- Grammatical Evolution and Creativity -- 1 Introduction -- 2 Evolutionary Computation and Creativity -- 2.1 Evolutionary Music -- 2.2 Other Applications -- 2.3 Types of Creativity -- 2.4 Designing a System -- 3 Case Study: The Composing Pony -- 3.1 Grammar -- 3.2 The Problem of Fitness -- 3.3 Self-Adaptive System -- 4 Case Study: Evolving Live Code -- 4.1 Live Coding -- 4.2 ChucK -- 4.3 Instrument Grammars -- 4.4 Generalised Grammar -- 4.5 Fitness Measure -- 5 Evaluation -- 5.1 Identifying the `Why?' -- 6 Conclusion -- References -- Identification of Models for Glucose Blood Values in Diabeticsby Grammatical Evolution -- 1 Introduction -- 2 Glucose models -- 3 Modeling Glycemia by Grammatical Evolution with Data Preprocessing -- 3.1 Using a Traditional SR Grammar -- 4 Enhancing Quality of Input Data with Data Augmentation -- 4.1 Moving Averages -- 4.2 Univariate Marginal Distribution Algorithm -- 4.3 Obtaining Models with Augmented Data -- 5 Why Grammatical Evolution? -- 6 Experimental Results -- 6.1 Experimental Environment -- 6.2 Results. , 6.2.1 Results with GE with Data Preprocessing.

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